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@article{rs16203821,

title = {Retrieval of Solar Shortwave Irradiance from All-Sky Camera Images},

author = {Daniel González-Fernández and Roberto Román and David Mateos and Celia Herrero del Barrio and Victoria E. Cachorro and Gustavo Copes and Ricardo Sánchez and Rosa Delia García and Lionel Doppler and Sara Herrero-Anta and Juan Carlos Antuña-Sánchez and África Barreto and Ramiro González and Javier Gatón and Abel Calle and Carlos Toledano and Ángel Frutos},

url = {https://www.mdpi.com/2072-4292/16/20/3821},

doi = {10.3390/rs16203821},

issn = {2072-4292},

year  = {2024},

date = {2024-10-14},

urldate = {2024-01-01},

journal = {Remote Sensing},

volume = {16},

number = {20},

abstract = {The present work proposes a new model based on a convolutional neural network (CNN) to retrieve solar shortwave (SW) irradiance via the estimation of the cloud modification factor (CMF) from daytime sky images captured by all-sky cameras; this model is named CNN-CMF. To this end, a total of 237,669 sky images paired with SW irradiance measurements obtained by using pyranometers were selected at the following three sites: Valladolid and Izaña, Spain, and Lindenberg, Germany. This dataset was randomly split into training and testing sets, with the latter excluded from the training model in order to validate it using the same locations. Subsequently, the test dataset was compared with the corresponding SW irradiance measurements obtained by the pyranometers in scatter density plots. The linear fit shows a high determination coefficient (R2) of 0.99. Statistical analyses based on the mean bias error (MBE) values and the standard deviation (SD) of the SW irradiance differences yield results close to ?2% and 9%, respectively. The MBE indicates a slight underestimation of the CNN-CMF model compared to the measurement values. After its validation, model performance was evaluated at the Antarctic station of Marambio (Argentina), a location not used in the training process. A similar comparison between the model-predicted SW irradiance and pyranometer measurements yielded R2=0.95, with an MBE of around 2% and an SD of approximately 26%. Although the precision provided by the SD at the Marambio station is lower, the MBE shows that the model’s accuracy is similar to previous results but with a slight overestimation of the SW irradiance. Finally, the determination coefficient improved to 0.99, and the MBE and SD are about 3% and 11%, respectively, when the CNN-CMF model is used to estimate daily SW irradiation values.},

keywords = {all-sky camera, Antarctica, cloud modification factor, convolutional neural network, shortwave global horizontal irradiance, sky images},

pubstate = {published},

tppubtype = {article}

}

@article{rs12223769,

title = {Characterization of Stratospheric Smoke Particles over the Antarctica by Remote Sensing Instruments},

author = {Ramiro González and Carlos Toledano and Roberto Román and David Mateos and Eija Asmi and Edith Rodríguez and Ian C Lau and Jonathan Ferrara and Raúl D’Elia and Juan Carlos Antuña-Sánchez and Victoria E Cachorro and Abel Calle and Ángel M de Frutos},

url = {https://www.mdpi.com/2072-4292/12/22/3769},

doi = {10.3390/rs12223769},

issn = {2072-4292},

year  = {2020},

date = {2020-01-01},

journal = {Remote Sensing},

volume = {12},

number = {22},

abstract = {Australian smoke from the extraordinary biomass burning in December 2019 was observed over Marambio, Antarctica from the 7th to the 10th January, 2020. The smoke plume was transported thousands of kilometers over the Pacific Ocean, and reached the Antarctic Peninsula at a hight of 13 km, as determined by satellite lidar observations. The proposed origin and trajectory of the aerosol are supported by back-trajectory model analyses. Ground-based Sun-Sky-Moon photometer belonging to the Aerosol Robotic Network (AERONET) measured aerosol optical depth (500 nm wavelength) above 0.3, which is unprecedented for the site. Inversion of sky radiances provide the optical and microphysical properties of the smoke over Marambio. The AERONET data near the fire origin in Tumbarumba, Australia, was used to investigate the changes in the measured aerosol properties after transport and ageing. The analysis shows an increase in the fine mode particle radius and a reduction in absorption (increase in the single scattering albedo). The available long-term AOD data series at Marambio suggests that smoke particles could have remained over Antarctica for several weeks after the analyzed event.},

keywords = {aerosol, Antarctica, Australian fires, biomass burning, optical properties, smoke ageing},

pubstate = {published},

tppubtype = {article}

}